Technologies for merging three-dimensional models of dental impressions

ABSTRACT

A computing device for dental impression scan merging includes a model manager configured to generate a first three-dimensional model and a second three-dimensional model, and a merge manager configured to merge the first model and the second model. Each model includes a respective plurality of geometric faces indicative of a respective dental impression of a dental arch of a user. Merging the first model and the second model includes aligning the first model and the second model, removing a geometric face of the first model, selecting a geometry of the second model corresponding with the removed geometric face of the first model, and generating a merged model that includes the selected geometry and the geometric faces corresponding to the selected geometry. The merged model is used to manufacture a dental aligner specific to the dental arch of the user and configured to reposition one or more teeth of the user.

CROSS REFERENCE TO RELATED PATENT APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 16/165,439 filed Oct. 19, 2018, which is a continuation of U.S.patent application Ser. No. 15/825,760 filed Nov. 29, 2017, now U.S.Pat. No. 10,109,114, each of which are incorporated by reference intheir entirety.

TECHNICAL FIELD

The present disclosure relates to three-dimensional computer modelingand, more specifically, to a system and method for mergingthree-dimensional models of dental impressions.

BACKGROUND

A dental impression provides a negative imprint of the teeth and tissuesin the mouth. The negative impression may then be utilized to produce aphysical or digital reproduction of the teeth, e.g., dentures andorthodontics. Generally, a dental tray having a viscous, thixotropicimpression material therein is fit over the dental arches of thepatient. The impression material sets to a solid, leaving an imprint ofthe structures in the mouth. When removed from the mouth, the impressionprovides a detailed and stable negative of the teeth. Optionally, theimpression is processed using digital scanning methods to create thedigital negative of the teeth.

Traditionally, dental impressions are made in a dental office andrequire significant time. The impressions are then delivered to anoutside vendor that utilizes the impression to form a positive model ofthe teeth. If the dental impression includes any errors, e.g., anincomplete impression of the teeth and tissues, the patient may berequired to return to the dental office to have a second impressionmade.

As an alternative method to traditional orthodontic procedures, in lesssevere cases, dental impressions may be made with an at-home dentalimpression kit. Such kits are generally prescribed by a dentalprofessional to qualified customers, e.g., in a dental office. The usermay then administer the contents of the dental impression kit at home.After completing the dental impressions, the kit is returned to thedental professional. Some at-home kits may be difficult to administerand/or may result in poor quality dental impressions.

SUMMARY

According to one aspect, disclosed is a computing device for dentalimpression scan merging. The computing device includes a model managerconfigured to generate a first model and a second model. The first modelincludes a three-dimensional model including a plurality of geometricfaces indicative of a first dental impression of a user's dental arch.The second model includes a three dimensional model including aplurality of geometric faces indicative of a second dental impression ofthe user's dental arch. The first dental impression and the seconddental impression are impressions of the same dental arch of the user.The computing device includes a merge manager. The model manager isconfigured to align the first model with the second model based on anocclusal surface of the first model and a corresponding occlusal surfaceof the second model. The model manager is configured to determinewhether a geometric face of the second model has a depth greater than ageometric face of the first model. The geometric face of the first modelis one of the nearest geometric faces to the geometric face of thesecond model. The model manager is configured to remove the geometricface on the first model responsive to the geometric face of the secondmodel having the depth greater than the geometric face of the firstmodel. The model manager is configured to select a geometry includingeach of the geometric faces corresponding thereto from the first modelor the second model. The selected geometry is associated with a commonanatomical location in the user's dental arch. The model manager isconfigured to generate a merged model in response to identification ofthe selected geometry. The merged model includes the selected geometryand corresponding geometric faces. The computing device includes amanufacturing manager configured to use the merged model formanufacturing a dental aligner specific to the user's dental arch andbeing configured to reposition one or more teeth of the user.

In some embodiments, the merge manager is further configured to alignthe second model with the first model. The merge manager is furtherconfigured to determine whether the geometric face of the first modelhas the depth greater than the geometric face of the second model. Thegeometric face of the second model is one of the nearest geometric facesto the geometric face of the first model. The merge manager is furtherconfigured to remove the geometric face of the second model responsiveto the geometric face of the first model having the depth greater thanthe geometric feature of the second model.

In some embodiments, for each geometric face of the second model, themerge manager is configured to determine whether the geometric face ofthe first model has a depth greater than the geometric face on thesecond model nearest thereto. The merge manager is further configured toremove the geometric face of the second model responsive to thegeometric face of the first model having the depth greater than thegeometric feature of the second model.

In some embodiments, when the merge manager aligns the first model andthe second model, the occlusal surface for the first model is alignedwith the occlusal surface of the second model such that the occlusalsurface of the second model is aligned and stacked beneath the occlusalsurface of the first model.

In some embodiments, generate the merged model includes combine at leastsome remaining geometric faces of the first model with remaininggeometric faces of the second model to form the merged model.

In some embodiments, the merge manager is further configured to apply asmoothing function to the merged model to fill voids in the merged modelfrom removing the geometric face of the first model.

In some embodiments, for each geometric face in the first model, themerge manager is configured to determine whether the geometric face ofthe second model has the depth greater than the geometric face of thefirst model nearest thereto. The merge manager is further configured toremove the geometric face of the first model responsive to the geometricface of the second model having the depth greater than the geometricfeature of the first model.

In some embodiments, the merge manager is configured to select theselected geometry and generate the merged model following removal ofgeometric faces.

In some embodiments, determine whether the geometric face of the secondmodel has the depth greater than the geometric face of the first modelproximate thereto includes identify, for the geometric face for thefirst model, the geometric face on the second model nearest to thegeometric face for the first model. Determine whether the geometric faceof the second model has the depth greater than the geometric face of thefirst model proximate thereto includes define a plane for the nearestgeometric face on the second model, the plane extending from a vertex ofthe geometric face and a normal vector for the vertex. Determine whetherthe geometric face of the second model has the depth greater than thegeometric face of the first model proximate thereto includes determininga distance between a vertex of the geometric face for the first modeland the plane.

In some embodiments, remove the geometric face on the first modelcomparing the distance between the vertex of the geometric face for thefirst model and the plane to a threshold, and remove the geometric faceon the first model when the distance satisfies the threshold.

According to another aspect, disclosed is a method for dental impressionscan merging. The method includes generating, by a computing device, afirst model and a second model. The first model includes athree-dimensional model including a plurality of geometric facesindicative of a first dental impression of a user's dental arch. Thesecond model includes a three dimensional model including a plurality ofgeometric faces indicative of a second dental impression of the user'sdental arch. The first dental impression and the second dentalimpression are impressions of the same dental arch of the user. Themethod further includes aligning the first model with the second modelbased on an occlusal surface for the first model and a correspondingocclusal surface of the second model. The method further includesdetermining whether a geometric face of the second model has a depthgreater than a geometric face of the first model. The geometric face ofthe first model is one of the nearest geometric faces to the geometricface of the second model. The method further includes removing thegeometric face on the first model responsive to the geometric face ofthe second model having the depth greater than the geometric feature ofthe first model. The method further includes selecting a geometryincluding each of the geometric faces corresponding thereto from thefirst model or the second model. The selected geometry is associatedwith a common anatomical location in the user's dental arch. The methodfurther includes generating a merged model in response to identificationof the selected geometry, wherein the merged model includes the selectedgeometry and corresponding remaining geometric faces. The method furtherincludes manufacturing a dental aligner specific to the user's dentalarch and being configured to reposition one or more teeth of the userusing the merged model.

In some embodiments, the method further includes aligning the occlusalsurface of the second model with the occlusal surface of the firstmodel. The method further includes determining whether the geometricface on the second model has the depth greater than the geometric faceon the second model. The method further includes removing the geometricface on the second model responsive to the geometric face of the firstmodel having the depth greater than the geometric feature on the secondmodel.

In some embodiments, generating the merged model includes combining atleast some remaining geometric faces of the first model with remaininggeometric faces of the second model to form the merged model.

In some embodiments, the method further includes applying a smoothingfunction to the merged model to fill voids in the merged model fromremoving the geometric face on the first model.

In some embodiments, the steps of determining whether the geometric faceon the second model has the depth greater than the geometric face on thefirst model proximate thereto and removing the geometric face on thefirst model responsive to the geometric face of the second model havingthe depth greater than the geometric feature on the first model areperformed for each geometric face in the first model.

In some embodiments, selecting the selected geometry is performedfollowing removal of geometric faces.

In some embodiments, the step of determining whether the geometric faceon the second model has the depth greater than the geometric face on thefirst model includes identifying, for the geometric face for the firstmodel, the geometric face on the second model nearest to the geometricface for the first model. The step further includes defining a plane forthe nearest geometric face on the second model, the plane extending froma vertex of the geometric face and a normal vector for the vertex. Thestep further includes determining a distance between a vertex of thegeometric face for the first model and the plane. The step furtherincludes determining that the geometric face on the second model has adepth greater than the geometric face on the first model when thedistance satisfies a threshold.

According to another aspect, disclosed is a computing device for dentalimpression scan merging. The computing device includes a processingcircuit including a processor and memory. The memory stores instructionsthat, when executed by the processor, cause the processor to generate afirst model and a second model. The first model includes athree-dimensional model including a plurality of geometric facesindicative of a first dental impression of a user's dental arch. Thesecond model includes a three dimensional model including a plurality ofgeometric faces indicative of a second dental impression of the user'sdental arch. The first dental impression and the second dentalimpression are impressions of the same dental arch of the user. Thememory further stores instructions to align the first model with thesecond model based on an occlusal surface of the first model and acorresponding occlusal surface of the second model. The memory furtherstores instructions to determine whether a geometric face of the secondmodel has a depth greater than a geometric face of the first model. Thegeometric face of the first model is one of the nearest geometric facesto the geometric face of the second model. The memory further storesinstructions to remove the geometric face on the first model responsiveto the geometric face of the second model having the depth greater thanthe geometric feature of the first model. The memory further storesinstructions to select a geometry including each of the geometric facescorresponding thereto from the first model or the second model. Theselected geometry is associated with a common anatomical location in theuser's dental arch. The memory further stores instructions to generate amerged model in response to identification of the selected geometry. Themerged model includes the selected geometry and corresponding remaininggeometric faces. The memory further stores instructions to manufacture adental aligner specific to the user's dental arch and being configuredto reposition one or more teeth of the user using the merged model.

In some embodiments, the memory further stores instructions to align theocclusal surface of the second model with the occlusal surface of thefirst model. The memory further stores instructions to determine whetherthe geometric face on the second model has the depth greater than thegeometric face on the second model. The memory further storesinstructions to remove the geometric face on the second model responsiveto the geometric face of the first model having the depth greater thanthe geometric feature on the second model.

In some embodiments, the memory stores instructions to perform, for eachgeometric face in the first model, the steps of determine whether thegeometric face on the second model has the depth greater than thegeometric face on the first model and, remove the geometric face on thefirst model responsive to the geometric face of the second model havingthe depth greater than the geometric feature on the first model.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other features of the various embodiments of themethods and apparatuses described herein will become more apparent fromthe following detailed description and the accompanying drawings inwhich:

FIG. 1 is a block diagram of at least one embodiment of a computingdevice for merging three-dimensional models;

FIG. 2 is a block diagram of at least one embodiment of an environmentthat may be established by the computing device of FIG. 1;

FIG. 3 is a flow diagram of at least one embodiment of a method forcapturing and processing three-dimensional scans of dental impressionsthat may be executed by the computing device of FIGS. 1 and 2;

FIG. 4 is a flow diagram of at least one embodiment of a method formerging three-dimensional models that may be executed by the computingdevice of FIGS. 1 and 2;

FIG. 5 is a user interface for uploading first and second models to bemerged;

FIG. 6 is a user interface showing a rough merge of the first and secondmodels of FIG. 5;

FIG. 7 is a user interface showing the occlusal surface of the first andsecond models of FIG. 5 for selecting correlation points in the twomodels;

FIG. 8 is a simplified representation of two three-dimensional modelsbeing merged;

FIG. 9 is a user interface depicting the merged model generated from thefirst and second models; and

FIG. 10 is a flow diagram of at least one embodiment of another methodof merging three-dimensional models that may be executed by thecomputing device of FIGS. 1 and 2.

DETAILED DESCRIPTION

While the concepts of the present disclosure are susceptible to variousmodifications and alternative forms, specific exemplary embodimentsthereof have been illustrated by way of example in the drawings and willherein be described in detail. It should be understood, however, thatthere is no intent to limit the concepts of the present disclosure tothe particular forms disclosed, but on the contrary, the intention is tocover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the disclosure as defined by the appendedclaims.

The disclosed embodiments may be implemented, in some cases, inhardware, firmware, software, or any combination thereof. The disclosedembodiments may also be implemented as instructions carried by or storedon a transitory or non-transitory machine-readable (e.g.,computer-readable) storage medium, which may be read and executed by oneor more processors. A machine-readable storage medium may be embodied asany storage device, mechanism, or other physical structure for storingor transmitting information in a form readable by a machine (e.g., avolatile or non-volatile memory, a media disc, or other media device).

Referring now to FIG. 1, an illustrative computing device 100 formerging three-dimensional models of dental impressions is shown. In use,as described further below, the computing device 100 generates orotherwise acquires three-dimensional models for each of multiple dentalimpressions. For example, multiple dental impressions created by a userwith an at-home dental impression kit may be scanned to generate thethree-dimensional models. The computing device 100 automatically mergesgeometry from the models to generate a complete model of one or more ofthe user's dental arches. In some embodiments, the computing device 100may use multiple merge strategies and select the best merged model.Thus, the computing device 100 may generate a higher-quality mergedmodel as compared to any of the individual models. Additionally, thecomputing device 100 may be able to generate a complete model frommultiple incomplete dental impressions, which may improve the proportionof at-home dental kits that are successfully completed and/or reduce thenumber of retake impression kits that are sent to users (e.g.,customers).

The computing device 100 may be embodied as any type of computation orcomputer device capable of performing the functions described herein,including, without limitation, a computer, a server, a workstation, adesktop computer, a laptop computer, a notebook computer, a tabletcomputer, a mobile computing device, a wearable computing device, anetwork appliance, a web appliance, a distributed computing system, aprocessor-based system, and/or a consumer electronic device. As such,the computing device 100 may be embodied as a single server computingdevice or a collection of servers and associated devices. For example,in some embodiments, the computing device 100 may be embodied as a“virtual server” formed from multiple computing devices distributedacross a network and operating in a public or private cloud.Accordingly, although the computing device 100 is illustrated in FIG. 1and described below as embodied as a single server computing device, itshould be appreciated that the computing device 100 may be embodied asmultiple devices cooperating together to facilitate the functionalitydescribed below.

As shown in FIG. 1, the computing device 100 illustratively include aprocessor 120, an input/output subsystem 122, a memory 124, a datastorage device 126, and a communication subsystem 128, and/or othercomponents and devices commonly found in a server computer or similarcomputing device. Of course, in other embodiments, the computing device100 may include other or additional components, such as those commonlyfound in a server computer (e.g., various input/output devices).Additionally, in some embodiments, one or more of the illustrativecomponents may be incorporated in, or otherwise form a portion of,another component. For example, the memory 124, or portions thereof, maybe incorporated in the processor 120.

The processor 120 may be embodied as any type of processor capable ofperforming the functions described herein. The processor 120 may beembodied as a single or multi-core processor(s), digital signalprocessor, microcontroller, or other processor or processing/controllingcircuit. Similarly, the memory 124 may be embodied as any type ofvolatile or non-volatile memory or data storage capable of performingthe functions described herein. In operation, the memory 124 may storevarious data and software used during operation of the computing device100, such as operating systems, applications, programs, libraries, anddrivers. The memory 124 is communicatively coupled to the processor 120via the I/O subsystem 122, which may be embodied as circuitry and/orcomponents to facilitate input/output operations with the processor 120,the memory 124, and other components of the computing device 100. Forexample, the I/O subsystem 122 may be embodied as, or otherwise include,memory controller hubs, input/ output control hubs, platform controllerhubs, integrated control circuitry, firmware devices, communicationlinks (i.e., point-to-point links, bus links, wires, cables, lightguides, printed circuit board traces, etc.) and/or other components andsubsystems to facilitate the input/output operations. In someembodiments, the I/O subsystem 122 may form a portion of asystem-on-a-chip (SoC) and be incorporated, along with the processor120, the memory 124, and other components of the computing device 100,on a single integrated circuit chip.

The data storage device 126 may be embodied as any type of device ordevices configured for short-term or long-term storage of data such as,for example, memory devices and circuits, memory cards, hard diskdrives, solid-state drives, or other data storage devices. Thecommunication subsystem 128 of the computing device 100 may be embodiedas any communication circuit, device, or collection thereof, capable ofenabling communications between the computing device 100 and otherremote devices over a network. The communication subsystem 128 may beconfigured to use any one or more communication technology (e.g., wiredor wireless communications) and associated protocols (e.g., Ethernet,InfiniBand®, Bluetooth®, WiMAX, etc.) to effect such communication.

As shown, the computing device 100 may also include one or moreperipheral devices 130. The peripheral devices 130 may include anynumber of additional input/output devices, interface devices, and/orother peripheral devices. For example, in some embodiments, theperipheral devices 130 may include a display, touch screen, graphicscircuitry, keyboard, mouse, speaker system, microphone, networkinterface, and/or other input/output devices, interface devices, and/orperipheral devices.

Referring now to FIG. 2, in an illustrative embodiment, the computingdevice 100 establishes an environment 200 during operation. Theillustrative environment 200 includes model manager 202, a scandispositioner circuitry 206, a merge manager 208, an impression manager212, and a manufacturing manager 214. The various components of theenvironment 200 may be embodied as hardware, firmware, software, or acombination thereof. As such, in some embodiments, one or more of thecomponents of the environment 200 may be embodied as circuitry orcollection of electrical devices (e.g., model manager circuitry 202,scan dispositioner circuitry 206, merge manager circuitry 208,impression manager circuitry 212, and/or manufacturing manager circuitry214). It should be appreciated that, in such embodiments, one or more ofthe model manager circuitry 202, the scan dispositioner circuitry 206,the merge manager circuitry 208, the impression manager circuitry 212,and/or the manufacturing manager circuitry 214 may form a portion of oneor more of the processor 120, the I/O subsystem 122, and/or othercomponents of the computing device 100. Additionally, in someembodiments, one or more of the illustrative components may form aportion of another component and/or one or more of the illustrativecomponents may be independent of one another.

The model manager 202 is configured to generate multiple models 204.Each model 204 may be embodied as a three-dimensional model indicativeof a dental impression of a client's dental arch (e.g., mandibular archor maxillary arch). The models 204 may be generated by scanning thecorresponding dental impression to generate the model 204. Althoughillustrated as a model of dental impressions, in some embodiments, eachmodel 204 may be embodied as a three-dimensional model of a differentphysical object. As described below, the model manager 202 may befurther configured to generate additional models 204 if a merged model204 is not indicative of the complete anatomy of a customer's dentalarch.

The scan dispositioner circuitry 206 is configured to determine whethera model 204 (including a merged model 204) is indicative of a completeanatomy of the customer's dental arch. That determination may be basedon quality review data provided for each model 204 by a technician.

The merge manager 208 is configured to merge two models 204 using amerge strategy 210 to generate a merged model 204 if an original inputmodel 204 is not indicative of the complete anatomy of the customer'sdental arch. Each merge strategy 210 may be embodied as any algorithm,process, policy, or other strategy that may be used to select geometryfrom the input models 204 to be included in the merged model 204. Insome embodiments, the merge manager 208 may be configured to merge themodels 204 using multiple merge strategies 210 to generate multiplemerge models 204. The merge manager 208 may be configured to select amerged model 204 from multiple results, for example, by receiving aselection of the best-merged model 204 from a technician.

To perform the merge, the merge manager 208 may be configured to aligngeometry of the models 204 based on a common point or other commonlocation. The merge manager 208 is configured to select geometry fromeither of the models 204 using the merge strategy 210. The selectedgeometry is associated with a common anatomical location in thecustomer's dental arch. Selecting the geometry using the merge strategy210 may include, for example, determining which of the dentalimpressions associated with the models 204 includes more detailassociated with the common anatomical location and/or determining whichof the models 204 includes greater depth associated with the commonanatomical location. In some embodiments, the merge strategy 210 mayinclude one or more of the steps described below with reference to FIG.5-FIG. 10. The merge manager 208 may be further configured to clean (orsmooth) the merged model 204 to generate a closed surface, for example,by performing Poisson surface reconstruction or by performing a gapclosing (or smoothing) algorithm.

The impression manager 212 may be configured to obtain additional dentalimpressions if the input models 204 and/or the merged model 204 do notinclude a complete representation of the customer's dental arch. Themanufacturing manager 214 may be configured to use the input models 204and/or the merged model 204 for sculpting and setup or otherwise use themodels 204 for manufacturing.

Referring now to FIG. 3, in use, the computing device 100 may execute amethod 300 for capturing and processing three-dimensional scans ofdental impressions. It should be appreciated that, in some embodiments,the operations of the method 300 may be performed by one or morecomponents of the environment 200 of the computing device 100 as shownin FIG. 2. The method 300 begins in block 302, in which the computingdevice 100 scans one or more dental impressions received from a customerto generate three-dimensional models 204. The computing device 100 mayuse any stereoscopic imager, photometric scanner, laser scanner,infrared scanner, structured light sensor, or other three-dimensionalscanning technology to scan the dental impressions. Each model 204 maybe embodied as a three-dimensional representation of the geometry of adental impression, which is in turn a negative representation of adental arch (e.g., a mandibular arch or maxillary arch) of the customer.Illustratively, the models 204 are embodied as standard trianglelanguage (STL) files that describe the surface geometry of thecorresponding dental impressions. In other embodiments, the models 204may be embodied as any surface or solid three-dimensional modeling data.

The computing device 100 may scan several impressions produced by thecustomer in connection with an at-home dental impression kit. Forexample, in some embodiments, in block 304, the computing device 100 mayscan two impressions for each of the customer's mandibular arch (i.e.,the customer's lower teeth) and the customer's maxillary arch (i.e., thecustomer's upper teeth), producing a total of four models 204.Additionally or alternatively, in some embodiments, the computing device100 may scan a different number of dental impressions. For example, asdescribed further below, a retake kit may include multiple dentalimpressions for one or more of the user's dental arches.

Additionally, although illustrated in FIG. 3 as scanning the dentalimpressions to generate the models 204, it should be understood that thecomputing device 100 may receive the models 204 from another device orotherwise acquire the models 204. For example, in some embodiments, thedental impressions may be scanned by a device located at a remoteimaging lab, mobile imaging lab, or other remote location.

In block 306, the computing device 100 removes excess geometry from eachmodel 204. The excess geometry may be removed, for example, by atechnician using a 3-D editor, or may be removed automatically.

In block 308, the computing device 100 receives quality review data foreach impression/scan from a technician. The technician may, for example,interactively view a representation of each model 204 and then providethe quality review data. The quality review data may indicate whetherthe corresponding dental impression includes a complete impression ofthe user's dental arch. Due to incorrect use by the customer or otherfactors, a dental impression may not include clear impressions of one ormore teeth or other areas of a dental arch. Thus, in some embodiments,the quality review data may identify incomplete areas of each arch(e.g., incomplete sides, teeth, or other parts of the impression).

In block 310, for each of the mandibular arch and the maxillary arch,the computing device 100 determines whether one of the models 204 iscomplete. For example, the computing device 100 may determine whetherany of the models 204 includes data for a complete impression of adental arch using the quality review data. In block 312, the computingdevice 100 checks whether a model 204 is complete for both of the dentalarches. If so, the method 300 branches ahead to block 322, describedbelow. If a model 204 is not complete for either arch, the method 300advances to block 314.

In block 314, for one or more of the dental arches, the computing device100 automatically merges incomplete models 204 to generate a mergedmodel 204. For example, the computing device 100 may merge two models204 of the customer's mandibular arch and/or may merge two models 204 ofthe customer's maxillary arch. The computing device 100 may use one ormore merge strategies 210 to select geometry from one of the models 204and replace geometry in the other model 204 with the selected geometry.Thus, after merging, the merged model 204 may include geometry generatedby scanning more than one physical object (e.g., from more than onedental impression). One potential embodiment of a method forautomatically merging the models 204 is described below in connectionwith FIG. 4.

In block 316, for each of the mandibular arch and the maxillary arch,the computing device 100 checks whether one of the models 204, includingthe merged model 204, is complete. If so, the method 300 branches aheadto block 322, described below. If a model 204 is not complete, themethod 300 advances to block 318.

In block 318, the computing device 100 obtains additional dentalimpressions for the incomplete dental arch(es). In some embodiments, inblock 320 the computing device 100 may cause a retake impression kit tobe sent to the customer. The retake impression kit may include materials(e.g., dental trays and thixotropic impression material) to create oneor more dental impressions for the incomplete dental arch or arches.After obtaining additional dental impressions, the method 300 loops backto block 302, in which the additional dental impressions may be scanned,checked for completeness, and potentially merged with the existingmodels 204.

Referring back to block 316, if a model 204 is complete for both of thedental arches, then the method 300 advances to block 322, in which thecomputing device 100 uses the complete models 204 of the customer'sdental arches to perform sculpting and setup. For example, a completemodel 204 may be used to generate a three-dimensional treatment plan forthe customer, to generate or manufacture a positive model of thecustomer's dental arches, and/or to manufacture invisible aligners forthe customer. After using the complete models 204, the method 300 iscompleted. The method 300 may be executed again for an additionalcustomer and/or for additional dental impressions.

Referring now to FIG. 4, in use, the computing device 100 may execute amethod 400 for merging three-dimensional models. The method 400 may beexecuted in connection with block 314 of FIG. 3, as described above. Itshould be appreciated that, in some embodiments, the operations of themethod 400 may be performed by one or more components of the environment200 of the computing device 100 as shown in FIG. 2. The method 400begins in block 402, in which the computing device 100 aligns thegeometry of multiple models 204. Each of the models 204 may be generatedfrom a scan of a dental impression of one of the customer's dentalarches. For example, the computing device 100 may merge two models 204associated with the mandibular arch of the customer or may merge twomodels 204 associated with the maxillary arch of the customer. Thegeometry of the models 204 is aligned according to the underlyinggeometry of the dental impressions and, therefore, the correspondinganatomy of the customer's dental arches. In some embodiments, in block404 the models 204 may be aligned to one or more common points selectedby a technician. For example, the technician may interactively identifyteeth or other common features in each of the models 204. In someembodiments, in block 406 the models 204 may be aligned automaticallyusing a best fit algorithm that compares the anatomy of the teethrepresented in each of the models 204.

After aligning the geometry, in block 408 the computing device 100selects geometry from the models 204 to include in a merged model 204using one or more merge strategies 210. The computing device 100 mayselect geometry from a model 204 to fill in incomplete parts of theother model 204. In some embodiments, in block 410, the computing device100 may select geometry from the model 204 corresponding to the dentalimpression that includes the most detail of the user's anatomy. Forexample, the computing device 100 may select geometry from a model 204of a dental impression that captures the customer's anatomy from the tipof the teeth to the gingival line.

In some embodiments, in block 412 the computing device 100 may comparethe models 204 and select geometry from the model 204 having thegreatest depth. In other words, the computing device 100 may selectgeometry from the model 204 with the greatest distance from the bottomof the impression (e.g., corresponding to the tip of a tooth) up to thetop of the impression (e.g., the surface of the impression mixture). Forexample, the computing device 100 may combine the models 204 intomultiple layers, and then select lower points from the layers. Havinglower depth in the model 204 indicates that the dental impression wasalso deeper, and deeper dental impressions tend to capture greaterdetail of the customer's tooth and gum anatomy. Additionally, using thedeeper model 204 may remove noise from the model 204, such as spikes inthe impression caused by the impression mixture pulling up as theimpression is removed from the customer's teeth.

In block 414, the computing device 100 generates the merged model 204including the selected geometry. The merged model 204 may include 3Dgeometry from both of the models 204, with the less-detailed componentsof the geometry removed.

In block 416, the computing device 100 may clean the merged model 204 togenerate a closed surface, also known as a watertight mesh. In someembodiments, the model 204 may be embodied as a mesh or other surfacemodel, and that mesh may include holes or be otherwise open. Generatinga closed surface may allow the merged model 204 to define a solid objectthat can, for example, be input to a 3-D printer. The computing device100 may use any technique to clean the merged model 204. In someembodiments, in block 418 the computing device 100 may perform Poissonsurface reconstruction to generate the closed surface. Additionally oralternatively, in some embodiments the computing device 100 may performa gap closing algorithm for surface reconstruction to generate theclosed surface.

In block 420, the computing device 100 determines whether multiple mergestrategies 210 were used to generate multiple merged models 204. Asdescribed above in connection with block 408, the computing device 100may use more than one merge strategy 210 to merge the models 204. Eachmerge strategy 210 may generate a different merged model 204. If asingle merge strategy 210 is used, the method 400 branches ahead toblock 426. If more than one merge strategy 210 is used, the method 400advances to block 422.

In block 422, the computing device 100 presents the merged and cleanedmodels 204 generated using the multiple merge strategies 210 to atechnician for review. In block 424, the computing device 100 receives aselection of a merged model 204 from the technician. The technician may,for example, manually select the best-merged model 204.

In block 426, the computing device 100 outputs the merged model 204. Asdescribed above in connection with FIG. 3, if the merged model 204 iscomplete, it may be used to prepare a three-dimensional treatment planfor the customer, to generate or manufacture a positive model of thecustomer's dental arches, to manufacture invisible aligners for thecustomer, or otherwise be used for dental treatment. After outputtingthe merged model 204, the method 400 is completed. The method 400 may beexecuted repeatedly to perform additional merges.

Referring now to FIG. 5-FIG. 7, various user interfaces are shown forgenerating a merged model 204, according to exemplary embodiments.Specifically, FIGS. 5-7 depict a series of user interfaces which may beused for merging two or more models 204 to output a merged model 204. Insome embodiments, the user interfaces may be operated, controlled, orotherwise used by a user of the computing device 100. In someembodiments, one or more of the steps outlined below may be automated(and thus the user interface corresponding to such steps may be omittedor modified).

FIG. 5 depicts a user interface for uploading models to be merged. Themodels may be represented in various file formats. For instance, themodels may be represented as geometric faces coupled to one anotheraccording to a surface contour. In some embodiments, the geometric facesmay be triangles (e.g., the file format may be STL). Each triangle maybe joined at the sides by adjacent triangles proximate thereto. Hence,the triangles form a mesh which represents the surface contour orgeometry of the user's mouth, or at least the user's teeth and gums (ascaptured by the dental impression or three-dimensional scan). Asdescribed above, the model manager 202 is configured to generate andstore multiple models 204. Such models 204 may include a first model 500and a second model 502. The first model 500 and second model 502 arerepresentations of the same dental arch of a user. For example, thefirst model 500 can be captured at a first time and the second model 502can be captured at a second time (e.g., shortly after the first model500 is captured).

In some embodiments, a user uploads the first model 500 and second model502 to the computing device 100 (e.g., for use by the model manager202). The user may select or otherwise provide an address to a filelocation corresponding to the first and second models 500, 502, drag anddrop the files corresponding to the models 500, 502 into a workspace, afile upload box, or other user interface element which may be used foruploading files to the computing device 100. In some embodiments, themodel manager 202 automatically retrieves the first and second models500, 502 (e.g., based on a creation time, based on a file name, etc.).In each of these embodiments, the model manager 202 receives, acquires,obtains, or otherwise generates and includes the first model 500 andsecond model 502.

The user may select (or the model manager 202 may automaticallyinitiate) a merge model option 504. The merge model option 504 is shownto be represented as a button (“Merge STLs”) on the user interface,though the merge model option 504 may be implemented in other ways viathe user interface.

Upon selection and/or initiation of the merge model option 504, themerge manager 208 may be configured to generate a rough merge 600 of themodel. FIG. 6 shows a rough merge of the first and second models 500,502, according to an exemplary embodiment. The merge manager 208 maygenerate the rough merge 600 in a number of ways. The merge manager 208may identify, estimate, etc., corresponding anatomical features betweenthe first model 500 and second model 502. For instance, the mergemanager 208 may match crowns in the first model 500 with crowns in thesecond model 502. The user is then prompted to select correlation pointsfor generating a more accurate merge than the rough merge 600, or formodifying the rough merge 600 prior to generating the more accuratemerge. A select points option 605 is shown on the user interface. Whilethe select points option 605 is shown to be represented on the userinterface as a button, the select points option 605 may be implementedin other ways via the user interface. Upon the select points option 605being selected by the user, the user may be prompted to selectcorrelation points between the two models 500, 502 for refining themerged model, as described in greater detail below.

Following the merge model option 504 being initiated (e.g., by the useror by the model manager 202), various corresponding points for the firstand second models 500, 502 are selected for aligning the models 500,502. The user interface shown in FIG. 7 depicts the occlusal surface700, 702 of the first and second models 500, 502, respectively, forselecting correlation points 704 in the two models 500, 502. Thecorrelation points 704 include a left point, an apex point, and a rightpoint for each model 500, 502. The left correlation point 704 on thefirst model 500 may be a point on the left side of the first model 500which correlates or corresponds to a correlation point 704 on the leftside of the second model 502. Similarly, the apex correlation point maybe a point towards the center of the first model 500 which correlates toa correlation point 704 towards the center of the second model 502, andthe right correlation point 704 on the first model 500 may be a point onthe right side of the first model 500 that correlates to a correlationpoint 704 on the right side of the second model 502. In someembodiments, a user selects the correlation points 704, for instance, bylocating a geometric feature on the first model 500, selecting thatgeometric feature on the first model 500, and locating and selecting asimilar, related, or corresponding geometric feature on the second model502. In some embodiments, the merge manager 208 selects the correlationpoints 704 (e.g., based on correlating geometric features in therespective models 500, 502). In each embodiment, a user may modify thelocation of the correlation points 704 based on the prominence ofgeometric features in the first and second models 500, 502 to betteralign the first and second models 500, 502. The user may select thecorrelation points 704 and drag the selected correlation points 704 todifferent locations as needed.

Once the correlation points 704 on the first model 500 and second model502 are selected, the first and second models 500, 502 are merged. Themerge manager 208 is configured to merge the first model 500 and secondmodel 502.

Referring now to FIG. 8, in some embodiments, the merge manager 208 isconfigured to align the occlusal surface 700 of the first model 500 withthe occlusal surface 702 of the second model 502. Specifically, FIG. 8shows simplified first and second models 800, 802 which are merged toform a merged model 900 (of FIG. 9). In some embodiments, the mergemanager 208 overlays the correlation points 704 for the first model 500and the correlation points 704 for the second model 502 to align thefirst model 500 and second model 500. As the merge manager overlays thecorrelation points 704 for the first model 500 and the correlationpoints 704 for the second model 502, each of the geometric faces for thefirst model 500 are overlaid on the second model 502. As such, the firstmodel 500 is stacked on top of and aligned with the second model 502.Where the models 500, 502 are the same, each of the geometric faces onthe first and second models may be aligned with corresponding geometricfaces and extend within the same plane. Where the models 500, 502deviate from one another, at least some of the geometric faces may notbe aligned, or may not extend within the same plane. Hence, somegeometric faces in the first model 500 may be offset from correspondinggeometric faces in the second model 502. The merge manager 208 isconfigured to apply various best fit calculations, which compare theanatomy of the scanned teeth, to more finely align the first and secondmodels 500, 502.

As shown in FIG. 8, and in some embodiments, the merge manager 208 isconfigured to determine whether a geometric face 804 of the second model802 has a depth greater than a geometric face 806 of the first model800. As can be seen in FIG. 8, the first model 800 has differentdimensions from the dimensions of the second model 802. As such, thegeometric faces 804, 806 are not aligned and does not extend within thesame plane.

The merge manager 208 is configured to selectively remove geometricfaces from the first and/or second model. The merge manager 208 isconfigured to selectively remove geometric faces from the first and/orsecond model based on relative depth of the geometric faces. In someembodiments, the merge manager 208 identifies corresponding geometricfaces for the first and second models 500, 502. For instance, when thefirst model 500 is stacked atop and aligned with the second model 502,the merge manager 208 may identify the nearest geometric faces for thefirst and second models 500, 502. Where the models 500, 502 are thesame, for a given geometric face for the first model 500, the nearestgeometric face on the second model 502 is aligned and extends in thesame plane. At locations where the first and second models 500, 502 arenot the same, corresponding geometric faces for the first model 500 andsecond model 502 will be slightly offset from one another.

The merge manager 208 may be configured to identify, for a givengeometric face of the first model 500, a corresponding geometric face onthe second model 502 which is nearest to the geometric face of the firstmodel 500. The merge manager 208 may be configured to identify thenearest face on the second model 502 for each geometric face on thefirst model 500.

As shown in FIG. 8, the geometric face 806 for the first model 800 andthe geometric face 804 for the second model 802 are offset. The mergemanager 208 may quantify the offset for the geometric faces 804, 806 fordetermining whether one of the first and second geometric faces 804, 806have a greater depth. The merge manager 208 is shown in FIG. 8 to definea plane 808 on the second model 802. In some embodiments, the mergermanager 208 defines a plane 808 within or corresponding to the geometricface 804 nearest to the geometric face 806 on the first model 800. Themerge manager 208 may identify a vertex 810 for the geometric face 804.The vertex 810 may be the peak (or maximum elevation) of the geometricface 804. The merge manager 208 may define the plane 808 based on thevertex 810. In some embodiments, the merge manager 208 defines the plane808 based on the identified vertex 810 and a normal vector 812 (e.g., aperpendicularly extending vector with respect to the vertex 810) for thevertex 810. Hence, the plane 808 in these embodiments extendsperpendicularly from the geometric face 804 and is aligned with thevertex 810.

In some embodiments, the merge manager 208 is configured to identify avertex 814 for the geometric face 806 of the first model 800 (e.g., thegeometric face 806 nearest to the geometric face 804). Similar to thevertex 810 of the second model 802, the vertex 814 of the first model800 may be the peak (or maximum elevation) of the geometric face 806.

The merge manager 208 is configured to determine a distance 816 betweenthe vertex 814 and the plane 808. The distance 816 may correspond to theoffset between the geometric faces 804, 806. In some embodiments, thedistance includes X, Y, and Z components (e.g., height, width, anddepth). The merge manager 208 may be used for determining relative depthof the first and second models 500, 502. In some embodiments, the mergemanager 208 compares the distance 816 between the vertex 814 and plane808 to a threshold. The threshold may correspond to a relative depthbetween the geometric faces 804, 806 corresponding to one another. Insome embodiments, the threshold is a minimum distance. The distance 816may satisfy the threshold when the distance 816 exceeds the minimumdistance. In other embodiments, the threshold is between a minimum andmaximum distance. Thus, the distance 816 may satisfy the threshold whenthe distance 816 falls between the minimum and maximum distance of thethreshold.

The merge manager 208 is configured to remove geometric faces on a givenmodel where a corresponding geometric face on the other model has agreater depth. For instance, the merge manager 208 may remove thegeometric face 806 on the first model 800 where the geometric face 804on the second model 802 has a greater depth (e.g., with respect to thegeometric face 806). In some embodiments, where the distance 816satisfies the threshold, the merge manager 208 may remove the geometricface 802 on the first model 800.

In some embodiments, the merge manager 208 is configured to identify therelative depth by casting a ray from each face on the first model 500 tonearby faces on the second model 502. The merge manager 208 may cast aray for each geometric face in the first model 500 to nearby faces onthe second model 502. The merge manager 208 may define a reverse facenormal plane or vector (e.g., a plane extending beneath andperpendicular) for a geometric face on the first model 500. The mergemanager 208 may cast the ray from the reverse face normal plane orvector towards the nearby geometric faces in the second model 502. Themerge manager 208 may determine whether any geometric faces on thesecond model 502 intersect with the ray (within a tolerance orthreshold, for instance). Where a face on the second model 502intersects with the ray, the merge manager 208 removes the geometricface on the second model 502.

The merge manager 208 may be configured to identify, determine, and/orquantify a depth between relative geometric faces for each of thegeometric faces of the first model 500. Hence, the merge manager 208 mayevaluate each of the geometric faces of the first model 500, and atleast some of those geometric faces may be removed. In some embodiments,the merge manager 208 may be configured to re-execute the steps outlinedabove with the first and second models 500, 502 reversed (e.g., wherethe second model 502 is stacked atop and aligned with the first model500). The merge manager 208 identifies nearest geometric faces on thefirst model 500 for a given geometric face on the second model 502,defines a plane for the first model, and identifies a distance betweenthe plane and a vertex of the geometric face on the second model.

In some embodiments, the merge manager 208 identifies geometric face(s)which are isolated in a geometric model 500, 502 (e.g., a givengeometric face is surrounded by voids where geometric faces wereremoved). The merge manager 208 may delete isolated geometric face(s).

Following such processing of the geometric models, the merge manager 208is configured to select a geometry. The selected geometry may be orinclude a selection of the first or second models 500, 502. The selectedgeometry may include the geometric faces remaining after removal of someof the geometric faces based on corresponding depth. The merge manager208 may select a geometry from the first and second models 500, 502based on remaining surface area, number of geometric faces remaining ineach model 500, 502, etc. The selected geometry may be used for formingthe merged model. In some embodiments, the merge manager 208incorporates, or combines, geometric faces from the unselected geometryinto the selected geometry (e.g., to fill gaps or voids within theselected geometry). The merge manager 208 may process the selectedgeometry to fill the gaps or voids. In some embodiments, the mergemanager 208 applies a smoothing function to the merged model. The mergemanager 208 may be further configured to clean or smooth the mergedmodel to generate a closed surface, for example, by performing Poissonsurface reconstruction or by performing a gap closing or smoothingalgorithm.

The merge manager 208 may be configured to render the merged model to auser, such as a dental technician, via a user interface. FIG. 9 shows auser interface depicting the merged model 900 generated from the firstand second models 500, 502. In some embodiments, the merge manager 208merges the first and second models 500, 502 according to a number ofdifferent merge strategies. The merge manager 208 may merge the firstand second models 500, 502 according to merge strategies that addressshifted scans, improper dental impression material mixtures, etc. Themerge manager 208 may be configured to automatically select the bestmerging strategy using, for instance, artificial intelligence, machinelearning, neural networks, etc. The merge manager 208 may, for instance,train a neural network for identifying which merging strategies resultin the best merged model.

In some embodiments, the merge manager 208 is configured to display eachof the merged models 900 to a user, such as a technician, on a displayor the user interface as shown in FIG. 9. In some embodiments, the userinterface includes an image of the patient's smile (e.g., correspondingto the dental impression). The image may be displayed side-by-side withthe merged model (and, optionally, the first and second models 500,502). The technician may select the ideal merged model based on theside-by-side photo. Following selection of the merged model for use, thetechnician may manipulate, modify, etc. the merged model to repositionthe patient's teeth, and the technician may export the modified mergedmodel to the manufacturing manager 214 for manufacturing dental alignersfor repositioning the patient's teeth, as described above.

Referring to FIG. 10, a flowchart depicting one embodiment of a method1000 for dental impression scan merging is shown, according to anexemplary embodiment. Similar to FIG. 3, it should be appreciated that,in some embodiments, the operations of the method 1000 may be performedby one or more components of the environment 200 of the computing device100 shown in FIG. 2.

At step 1005, the computing device 100 generates a first model andsecond model. In some embodiments, the computing device 100 scans one ormore dental impressions received from a customer to generatethree-dimensional models 204. Hence, the first model may be athree-dimensional model including a plurality of geometric facesindicative of a first dental impression of a user's dental arch, and thesecond model may be a three-dimensional model including a plurality ofgeometric faces indicative of a second dental impression of the user'sdental arch (e.g., the same dental arch). The computing device 100 mayuse any stereoscopic imager, photometric scanner, laser scanner,infrared scanner, structured light sensor, or other three-dimensionalscanning technology to scan the dental impressions. Each model 204 maybe embodied as a three-dimensional representation of the geometry of adental impression, which is in turn a negative representation of adental arch (e.g., a mandibular arch or maxillary arch) of the customer.Illustratively, the models 204 are embodied as STL files that describethe surface geometry of the corresponding dental impressions and includegeometric faces which form a mesh which defines the surface geometry orcontours. In other embodiments, the models 204 may be embodied as anysurface or solid three-dimensional modeling data.

At step 1010, and in some embodiments, the computing device 100 alignsan occlusal surface 700 of the first model 500 with an occlusal surface702 of the second model 502. In some embodiments, the computing device100 analyzes geometric properties of the first and second models 500,502 for aligning the occlusal surfaces 700, 702. In some embodiments,the computing device 100 receives or automatically selects correlationpoints 704 on the first and second models 500, 502. The computing device100 may overlay the correlation points 704 and remaining portions of thefirst and second models 500, 502. The computing device 100 may align theocclusal surfaces 700, 702 such that at least some of the geometricfaces in the first and second models 500, 502 are aligned and extend inthe same plane. Where the first and second models 500, 502 are differentfrom one another, the geometric faces may be offset from one another.For instance, some geometric faces on one model may correspond togreater measured or captured depths than in the other model.

At step 1015, and in some embodiments, the computing device 100 selectsa geometric face on the first model 500. The computing device 100 mayprogressively select geometric faces on the first model 500 beginning inone area (e.g., the right side, the center or apex, etc.), and progressthrough the geometric faces in the first model 500, as described ingreater detail below.

At step 1020, and in some embodiments, the computing device 100identifies a geometric face on the second model 502 nearest to thegeometric face selected at step 1015. In embodiments where the first andsecond models 500, 502 are the same, the nearest geometric face on thesecond model 502 is directly aligned with and extends planar to thegeometric face selected at step 1015. In embodiments where the models500, 502 are not the same, the identified geometric face on the secondmodel 502 nearest to the geometric face selected at step 1015 may beslightly offset from one another.

At step 1025, and in some embodiments, the computing device 100 maydetermine whether the geometric face on the second model 502 has a depthgreater than the geometric face on the first model 500. In someembodiments, the computing device 100 may define a plane on the secondmodel 500. Specifically, the computing device 100 defines a plane on thegeometric face on the second model 500. The plane may extend along thevertex for the geometric face and a normal vector for the vertex. Hence,the plane may extend outwardly from (e.g., perpendicularly to) and alongthe vertex of the geometric face. The computing device 100 may determinea distance between the vertex of the geometric face on the first model500 and the plane. The computing device 100 may compare the distance toa threshold (e.g., a minimum distance, a range of distances, etc.). Insome embodiments, the merge manager 208 identifies the relative depth bycasting a ray from the geometric face on the first model 500 to thegeometric face on the second model 502. The computing device 100 maydefine a reverse face normal plane or vector (e.g., a plane extendingbeneath and perpendicular) from the geometric face on the first model500. The computing device 100 may cast a ray from the reverse facenormal plane or vector to the geometric face on the second model 502.The merge manager 208 may determine whether the geometric face on thesecond model 502 intersects with the ray (e.g., within a tolerance orthreshold, for instance). Where the geometric face on the second model502 intersects with the ray, the computing device 100 may determine thatthe geometric face on the second model 502 has a greater depth.

Where the computing device 100 determines that the geometric face on thesecond model 502 has a depth greater than the geometric face on thefirst model 500, the method 1000 proceeds to step 1030. Where thecomputing device 100 determines that the geometric face on the secondmodel 502 does not have a depth greater than the geometric face on thefirst model 500 (or the distance or depth do not satisfy a threshold),the method 1000 proceeds to step 1035.

At step 1030, and in some embodiments, the computing device 100 removesthe geometric face on the first model 500. The computing device 100 mayremove the geometric face on the first model 500 when the correspondinggeometric face on the second model 502 has a greater depth. Thecomputing device 100 may remove the geometric face on the first model500 when the distance between the plane on the second model 502 and thevertex of the first model 500 satisfies a threshold (e.g., the vertex isgreater than a minimum distance, falls within a range of distances,etc.) corresponding to relative depth. The computing device 100 mayremove the geometric face on the first model 500 when the ray cast froma reverse face plane or vector intersects with the geometric face on thesecond model 502.

At step 1035, the computing device 100 may determine whether allgeometric faces on the first model 500 have been analyzed. The computingdevice 100 may maintain a data log of each geometric face as therelative depth between the geometric face of the first and second models500, 502 are determined. Where the computing device 100 determines thatall geometric faces on the first model 500 have been analyzed, themethod 1000 may proceed to step 1040. Where geometric faces have notbeen analyzed, the method 1000 may proceed back to step 1015, e.g.,where the computing device 100 selects another geometric face of thefirst model 500. Hence, the method may loop between step 1015-1035 untilall geometric faces of the first model 500 are analyzed.

At step 1040, the computing device 100 aligns the occlusal surface 702of the second model 502 with the occlusal surface 700 of the first model500. Following alignment, the second model and first model 500, 502 arereversed (e.g., with respect to the orientation at step 1010). In thisregard, the first and second models 500, 502 are flipped. The first andsecond models 500, 502 are aligned, except that the second model 502 ison top of the first model 500 at step 1040. Following step 1040, themethod 1000 may proceed to steps 1045-1065, which are similar to steps1015-1035 described above.

Following analysis of each of the geometric faces on the second model(e.g., step 1065), the method 1000 proceeds to step 1070. At step 1070,the computing device 100 selects a geometry. The selected geometry maybe or include a selection of the first or second models 500, 502. Theselected geometry may include the geometric faces remaining afterremoval of some of the geometric faces based on corresponding depth. Thecomputing device 100 may select a geometry from the first and secondmodels 500, 502 based on remaining surface area, number of geometricfaces remaining in each model 500, 502, etc. The selected geometry maybe used for forming the merged model.

At step 1075, and in some embodiments, the computing device 100generates the merged model. The computing device 100 may combineremaining geometric faces from the first and/or second model 500, 502into the selected geometry. In some embodiments, the computing device100 incorporates, or combines, geometric faces from the unselectedgeometry into the selected geometry (e.g., to fill gaps or voids withinthe selected geometry). The computing device 100 may process theselected geometry to fill the gaps or voids. In some embodiments, thecomputing device 100 applies a smoothing function to the merged model.The computing device 100 may be further configured to clean or smooththe merged model to generate a closed surface, for example, byperforming Poisson surface reconstruction or by performing a gap closingor smoothing algorithm.

The construction and arrangement of the systems and methods as shown inthe various exemplary embodiments are illustrative only. Although only afew embodiments have been described in detail in this disclosure, manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, orientations,etc.). By way of example, the position of elements may be reversed orotherwise varied and the nature or number of discrete elements orpositions may be altered or varied. Accordingly, all such modificationsare intended to be included within the scope of the present disclosure.The order or sequence of any process or method steps may be varied orre-sequenced according to alternative embodiments. Other substitutions,modifications, changes, and omissions may be made in the design,operating conditions and arrangement of the exemplary embodimentswithout departing from the scope of the present disclosure.

The present disclosure contemplates methods, systems and programproducts on memory or other machine-readable media for accomplishingvarious operations. The embodiments of the present disclosure may beimplemented using existing computer processors, or by a special purposecomputer processor for an appropriate system, incorporated for this oranother purpose, or by a hardwired system. Embodiments within the scopeof the present disclosure include program products or memory comprisingmachine-readable media for carrying or having machine-executableinstructions or data structures stored thereon. Such machine-readablemedia may be any available media that may be accessed by a generalpurpose or special purpose computer or other machine with a processor.By way of example, such machine-readable media can comprise RAM, ROM,EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to carry or store desired program code in the form ofmachine-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer or othermachine with a processor. Combinations of the above are also includedwithin the scope of machine-readable media. Machine-executableinstructions include, by way of example, instructions and data whichcause a general purpose computer, special purpose computer, or specialpurpose processing machines to perform a certain function or group offunctions.

Although the figures may show a specific order of method steps, theorder of the steps may differ from what is depicted. Also, two or moresteps may be performed concurrently or with partial concurrence. Suchvariation will depend on the software and hardware systems chosen and ondesigner choice. All such variations are within the scope of thedisclosure. Likewise, software implementations could be accomplishedwith standard programming techniques with rule based logic and otherlogic to accomplish the various connection steps, processing steps,comparison steps and decision step.

What is claimed is:
 1. A computing device for dental impression scanmerging, the computing device comprising: a model manager configured togenerate a first model and a second model, the first model comprising afirst three-dimensional model including a first plurality of geometricfaces indicative of a first dental impression of a dental arch of auser, the second model comprising a second three-dimensional modelincluding a second plurality of geometric faces indicative of a seconddental impression of the same dental arch of the user; a merge managerconfigured to merge the first model and the second model, whereinmerging the first model and the second model comprises: aligning thefirst model and the second model based on an occlusal surface of thefirst model and a corresponding occlusal surface of the second model;removing a geometric face of the first model based on a geometric faceof the second model that corresponds to the geometric face of the firstmodel having a depth greater than the geometric face of the first model;selecting a geometry of the second model corresponding with the removedgeometric face of the first model, the selected geometry of the secondmodel including geometric faces of the second plurality of geometricfaces; and generating a merged model that includes the selected geometryand the geometric faces corresponding to the selected geometry; amanufacturing manager configured to use the merged model formanufacturing a dental aligner specific to the dental arch of the userand being configured to reposition one or more teeth of the user.
 2. Thecomputing device of claim 1, wherein the merge manager is configured toremove a geometric face of the second model based on a geometric face ofthe first model that corresponds to the geometric face of the secondmodel having a depth greater than the geometric face of the secondmodel.
 3. The computing device of claim 2, wherein the merge manager isconfigured to remove each geometric face of the second model that has adepth less than a depth of one of the nearest geometric faces of thefirst model.
 4. The computing device of claim 1, wherein aligning thefirst model and the second model causes an occlusal surface of the firstmodel to be aligned with an occlusal surface of the second model.
 5. Thecomputing device of claim 1, wherein generating the merged modelcomprises combining at least some remaining geometric faces of the firstmodel with remaining geometric faces of the second model.
 6. Thecomputing device of claim 1, wherein the merge manager is configured tofill voids in the merged model caused by removing the geometric face ofthe first model by applying a smoothing function to the merged model. 7.The computing device of claim 1, wherein the merge manager is configuredto remove each geometric face of the first model that has a depth lessthan a depth of one of the nearest geometric faces of the second model.8. The computing device of claim 1, wherein the occlusal surface of thefirst model and the corresponding occlusal surface of the second modelare identified by an input received by a user interface, the inputindicative of an operator selection of points on the first model thatcorrelate with an operator selection of points on the second model. 9.The computing device of claim 8, wherein the operator selection ofpoints on the first model include a point in a first portion and a pointin a second portion of the first model, and wherein the operatorselection of points on the second model include a point in a firstportion and a point in a second portion of the second model.
 10. Thecomputing device of claim 9, wherein the first portion of the firstmodel and the first portion of the second model are right portions ofthe respective model, and wherein the second portion of the first modeland the second portion of the second model are left portions of therespective model.
 11. A method comprising: generating, by a computingdevice, a first model and a second model, the first model comprising afirst three-dimensional model including a first plurality of geometricfaces indicative of a first dental impression of a dental arch of auser, the second model comprising a second three-dimensional modelincluding a second plurality of geometric faces indicative of a seconddental impression of the same dental arch of the user; aligning thefirst model and the second model based on an occlusal surface of thefirst model and a corresponding occlusal surface of the second model;removing a geometric face of the first model based on a geometric faceof the second model that corresponds to the geometric face of the firstmodel having a depth greater than the geometric face of the first model;selecting a geometry of the second model corresponding with the removedgeometric face of the first model, the selected geometry of the secondmodel including geometric faces of the second plurality of geometricfaces; generating a merged model that includes the selected geometry andthe geometric faces corresponding to the selected geometry; andmanufacturing a dental aligner based on the merged model, the dentalaligner being specific to the dental arch of the user and beingconfigured to reposition one or more teeth of the user.
 12. The methodof claim 11, further comprising removing a geometric face of the secondmodel based on a geometric face of the first model that corresponds tothe geometric face of the second model having a depth greater than thegeometric face on the second model.
 13. The method of claim 11, whereingenerating the merged model comprises combining at least some remaininggeometric faces of the first model with remaining geometric faces of thesecond model.
 14. The method of claim 11, further comprising fillingvoids in the merged model caused by removing the geometric face of thefirst model by applying a smoothing function to the merged model. 15.The method of claim 11, wherein removing the geometric face comprisesremoving each geometric face of the second model that has a depth lessthan a depth of one of the nearest geometric faces of the first model.16. The method of claim 11, wherein selecting the geometry is performedfollowing removal of the geometric face of the first model.
 17. Themethod of claim 11, further comprising determining whether the geometricface of the second model has a depth greater than the geometric face ofthe first model, the determination comprising: identifying the geometricface of the second model nearest to the geometric face of the firstmodel; defining a plane of the nearest geometric face of the secondmodel, the plane extending from a vertex of the geometric face of thesecond model and a normal vector of the vertex; and determining adistance between a vertex of the geometric face of the first model andthe plane.
 18. A computing device for dental impression scan merging,the computing device comprising: a processing circuit including aprocessor and memory, the memory storing instructions that areconfigured to be executed by the processor to cause the processor to:generate a first model and a second model, the first model comprising afirst three-dimensional model including a first plurality of geometricfaces indicative of a first dental impression of a dental arch of theuser, the second model comprising a second three-dimensional modelincluding a second plurality of geometric faces indicative of a seconddental impression of the same dental arch of the user; align the firstmodel and the second model based on an occlusal surface of the firstmodel and a corresponding occlusal surface of the second model; remove ageometric face of the first model based on a geometric face of thesecond model that corresponds to the geometric face of the first modelhaving a depth greater than the geometric face of the first model;select a geometry of the second model corresponding with the removedgeometric face of the first model, the selected geometry of the secondmodel including the geometric faces of the second plurality of geometricfaces; generate a merged model that includes the selected geometry andthe geometric faces corresponding to the selected geometry; andmanufacture a dental aligner based on the merged model, the dentalaligner being specific to the dental arch of the user and beingconfigured to reposition one or more teeth of the user.
 19. Thecomputing device of claim 18, wherein the memory further storesinstructions that are configured to be executed by the processor tocause the processor to remove a geometric face of the second model basedon a geometric face of the first model that corresponds to the geometricface of the second model having a depth greater than the geometric faceon the second model.
 20. The computing device of claim 18, wherein thememory further stores instructions that are configured to be executed bythe processor to cause the processor to remove each geometric face ofthe second model that has a depth less than a depth of one of thenearest geometric faces of the first model.